System and method for satellite optical ground radio hybrid lightning location

ABSTRACT

Described herein are methods and systems for locating lightning activity. A server computing device receives, from a satellite that detects lightning activity occurring in a geographic region, location coordinates and time data associated with lightning activity detected by the satellite. The server captures, from at least one of one or more ground-based lightning sensors that detect lightning activity, lightning feature data for lightning activity detected by the at least one of one or more ground-based lightning sensors. The server computing device determines a location of the lightning activity within the geographic region using the lightning feature data and the location coordinates and time data. The server computing device transmits the determined location of the lightning activity to one or more remote computing devices.

TECHNICAL FIELD

This application claims priority to U.S. Provisional Patent ApplicationNo. 62/500,158, filed on May 2, 2017, the contents of which areincorporated herein by reference.

TECHNICAL FIELD

This application relates generally to systems and methods, includingcomputer program products, for satellite optical ground radio hybridlightning location.

BACKGROUND

Both satellite and ground based lightning location systems (LLS's)exist, and operate in different ways. Generally, satellite lightninglocation systems measure the light emitted by lightning usingcamera-like sensors to locate the flash. Typical ground-based lightninglocation systems (such as the Earth Networks Total Lightning Networkfrom Earth Networks, Inc.) measure the radio frequency radiation oflightning in multiple locations, and use time of arrival triangulationtechniques to locate the lightning flash.

Just recently, satellite-based LLS's have become useful for theoperational detection of lightning with the launch of the GeostationaryLightning Mapper (GLM) over the United States. Previously, satelliteLLS's orbited at low Earth orbit, and only provided a limited period ofcoverage for any specific location during a day (approximately 15minutes). Because the GLM is in geostationary orbit, its field of viewdoes not change with time, allowing it to provide continuous coverage.

However, ground and satellite LLS's each have certain strengths andweaknesses. Ground-based systems typically have non-uniform detectionefficiency (DE), and satellite systems have more uniform high DE. Thisis because the sensitivity/signal-to-noise ratio (SNR) of ground systemsdepends on how far one is away from the sensors, and for the satellitesystems sensitivity is constant and SNR changes with the backgroundlight levels (i.e., lower during the daytime, higher at night). DE ofground-based systems can be higher than satellites if the ground sensordensity is high enough, but far away from the sensors (such as over theocean) it tends not to be.

Satellite systems have lower location accuracy because they areimage-based systems. The location accuracy is a function of the numberof charge-coupled device (CCD) pixels and the field of view of the lens.For example, on the GLM, one pixel collects light from about a 10×10 kmsquare on the Earth. Ground based systems routinely locate lightningwith much better accuracy than that. It is possible to increase thenumber of pixels on the GLM, but doing so increases cost and reducesSNR.

SUMMARY

Therefore, what is needed are methods and systems for satellite opticalground radio hybrid lightning location that take advantage of thestrengths of the satellite system and of the ground-based system toproduce more accurate and efficient lightning location. The hybridlightning location system described herein has the DE of the satellitesystem, and the LA of the ground-based system. In addition,computational requirements for the ground-based portion of the hybridlightning location system can be reduced, as the satellite portion ofthe hybrid system identifies which radio features are produced by thesame lightning process, overcoming a major difficulty in existingground-based location techniques. Alternatively, the hybrid lightninglocation system can be used to relax the noise reduction algorithmsroutinely used by LLS's in isolation, by looking for two independentdetections.

The invention, in one aspect, features a computerized method of locatinglightning activity. A server computing device receives, from a satellitethat detects lightning activity occurring in a geographic region,location coordinates and time data associated with lightning activitydetected by the satellite. The server computing device captures, from atleast one of one or more ground-based lightning sensors that detectlightning activity, lightning feature data for lightning activitydetected by the at least one of one or more ground-based lightningsensors. The server computing device generates a plurality of groundpoint locations based upon the lightning feature data captured from theground-based lightning sensors. The server computing device compares theground point locations and the location coordinates received from thesatellite to identify one or more sets of matched data. The servercomputing device augments, for each set of matched data, the locationcoordinates for the lightning activity received from the satellite withthe lightning feature data captured from the ground-based sensors. Theserver computing device transmits the augmented location coordinates forthe lightning activity to one or more remote computing devices.

The invention, in another aspect, features a system for locatinglightning activity. The system comprises a server computing deviceincluding a memory for storing computer-executable instructions and aprocessor for executing the computer-executable instructions. Theprocessor executes the computer-executable instructions to receive, froma satellite that detects lightning activity occurring in a geographicregion, location coordinates and time data associated with lightningactivity detected by the satellite. The processor executes thecomputer-executable instructions to capture, from at least one of one ormore ground-based lightning sensors that detect lightning activity,lightning feature data for lightning activity detected by the at leastone of one or more ground-based lightning sensors. The processorexecutes the computer-executable instructions to generate a plurality ofground point locations based upon the lightning feature data capturedfrom the ground-based lightning sensors. The processor executes thecomputer-executable instructions to compare the ground point locationsand the location coordinates received from the satellite to identify oneor more sets of matched data. The processor executes thecomputer-executable instructions to augment, for each set of matcheddata, the location coordinates for the lightning activity received fromthe satellite with the lightning feature data captured from theground-based sensors. The processor executes the computer-executableinstructions to transmit the augmented location coordinates for thelightning activity to one or more remote computing devices.

Either of the above aspects can include one or more of the followingfeatures. In some embodiments, the server computing device receivesoptical energy information associated with the detected lightningactivity from the satellite. In some embodiments, the lightning featuredata captured from the ground-based lightning sensors comprises radiosferic data.

In some embodiments, generating a plurality of ground point locationscomprises combining the radio sferic data received from a plurality ofthe ground-based lightning sensors and processing the combined datausing a time of arrival triangulation algorithm to generate the groundpoint locations. In some embodiments, each ground point locationcomprises a location, a classification, an estimated peak current, andan estimated location accuracy.

In some embodiments, the comparing step comprises determining that alightning event detected by one or more of the ground-based sensorsoccurred within a predetermined time of a lightning event detected bythe satellite and occurred within a predetermined distance from thelightning event detected by the satellite. In some embodiments, theaugmenting step comprises appending geographic coordinates, peakcurrent, and classification from the ground-based sensors to group dataassociated with the satellite.

In some embodiments, the comparing step comprises determining that alightning event detected by one or more of the ground-based sensorsoccurred within a predetermined time of a lightning event detected bythe satellite, occurred outside a first predetermined distance from thelightning event detected by the satellite, and occurred inside a secondpredetermined distance of the lightning event detected by the satellite.In some embodiments, the augmenting step comprises appending peakcurrent, and classification from the ground-based sensors to group dataassociated with the satellite.

In some embodiments, the comparing step comprises determining that alightning event detected by one or more of the ground-based sensorsoccurred outside of a predetermined time of a lightning event detectedby the satellite or occurred outside a predetermined distance from thelightning event detected by the satellite. In some embodiments, theaugmenting step comprises leaving group data associated with thesatellite unchanged.

In some embodiments, generating a plurality of ground point locationsfurther comprises: determining a distance from the location coordinatesreceived from the satellite to a location of each of the ground-basedsensors; obtaining the radio sferic data from each ground-based sensorthat is located within a predetermined distance from the locationcoordinates received from the satellite; determining an expected arrivaltime of the radio sferic data obtained from the ground-based sensors;combining the radio sferic data that has an expected arrival time withina predetermined threshold into a collection of radio sferic data; anddetermining a location of lightning activity associated with the radiosferic data. In some embodiments, determining a location of lightningactivity associated with the radio sferic data comprises: a) finding apeak time (tp) and a sensor location (ps) for each radio sferic in thecollection of radio sferic data; b) assigning the geographic coordinates(p0) and time data (t0) received from the ground-based sensors as aninitial guess location; c) determining location (p) and time (t) for thelightning process using the collection of radio sferic data thatminimizes |t−D(p, ps)/c−tp|; d) determining a residual value (r) for allradio sferics in the collection of radio sferic data using the equation:r=t−D(p, ps)/c−tp; e) if (r) is below a predefined value for each radiosferic, identifying a location of the lightning activity based upon thedetermined locations for the radio sferics; and f) if (r) is not below apredefined value for at least one radio sferic, removing radio sfericsfrom the collection of radio sferic data that have a residual value (r)above the predefined value and returning to step c).

The invention, in another aspect, features a computerized method oflocating lightning activity. A server computing device receives, from asatellite that detects lightning activity occurring in a geographicregion, location coordinates and time data associated with lightningactivity detected by the satellite. The server computing devicecaptures, from at least one of one or more ground-based lightningsensors that detect lightning activity, lightning feature data forlightning activity detected by the at least one of one or moreground-based lightning sensors. The server computing device identifiesat least one of the one or more ground-based lightning sensors inproximity to the geographic region based upon the location coordinatesand time data received from the satellite. The server computing devicedetermines a location of the lightning activity using the lightningfeature data from the identified ground-based lightning sensors. Theserver computing device transmits the location of the lightning activityto one or more remote computing devices.

The invention, in another aspect, features a system of locationlightning activity. The system comprises a server computing deviceincluding a memory for storing computer-executable instructions and aprocessor for executing the computer-executable instructions. Theprocessor executes the computer-executable instructions to receive, froma satellite that detects lightning activity occurring in a geographicregion, location coordinates and time data associated with lightningactivity detected by the satellite. The processor executes thecomputer-executable instructions to capture, from at least one of one ormore ground-based lightning sensors that detect lightning activity,lightning feature data for lightning activity detected by the at leastone of one or more ground-based lightning sensors. The processorexecutes the computer-executable instructions to identify at least oneof the one or more ground-based lightning sensors in proximity to thegeographic region based upon the location coordinates and time datareceived from the satellite. The processor executes thecomputer-executable instructions to determine a location of thelightning activity using the lightning feature data from the identifiedground-based lightning sensors. The processor executes thecomputer-executable instructions to transmit the location of thelightning activity to one or more remote computing devices.

Either of the above aspects can include one or more of the followingfeatures. In some embodiments, the server computing device receivesoptical energy information associated with the detected lightningactivity from the satellite. In some embodiments, the lightning featuredata captured from the ground-based lightning sensors comprises radiosferic data.

In some embodiments, determining a location of the lightning activitycomprises determining that a lightning event detected by one or more ofthe ground-based sensors occurred within a predetermined time of alightning event detected by the satellite and occurred within apredetermined distance from the lightning event detected by thesatellite. In some embodiments, the server computing device appendsgeographic coordinates, peak current, and classification from theidentified ground-based sensors to group data associated with thesatellite.

In some embodiments, determining a location of the lightning activitycomprises determining that a lightning event detected by one or more ofthe ground-based sensors occurred within a predetermined time of alightning event detected by the satellite, occurred outside a firstpredetermined distance from the lightning event detected by thesatellite, and occurred inside a second predetermined distance of thelightning event detected by the satellite. In some embodiments, theserver computing device appends peak current, and classification fromthe identified ground-based sensors to group data associated with thesatellite.

In some embodiments, determining a location of the lightning activitycomprises determining that a lightning event detected by one or more ofthe ground-based sensors occurred outside of a predetermined time of alightning event detected by the satellite or occurred outside apredetermined distance from the lightning event detected by thesatellite. In some embodiments, the server computing device leaves groupdata associated with the satellite unchanged.

In some embodiments, identifying at least one of the one or moreground-based lightning sensors in proximity to the geographic regioncomprises: determining a distance from the location coordinates receivedfrom the satellite to a location of each of the ground-based sensors;obtaining the radio sferic data from each ground-based sensor that islocated within a predetermined distance from the location coordinatesreceived from the satellite; determining an expected arrival time of theradio sferic data obtained from the ground-based sensors; and combiningthe radio sferic data that has an expected arrival time within apredetermined threshold into a collection of radio sferic data. In someembodiments, identifying at least one of the one or more ground-basedlightning sensors in proximity to the geographic region furthercomprises: a) finding a peak time (tp) and a sensor location (ps) foreach radio sferic in the collection of radio sferic data; b) assigningthe geographic coordinates (p0) and time data (t0) received from theground-based sensors as an initial guess location; c) determininglocation (p) and time (t) for the lightning process using the collectionof radio sferic data that minimizes |t−D(p, ps)/c−tp|; d) determining aresidual value (r) for all radio sferics in the collection of radiosferic data using the equation: r=t−D(p, ps)/c−tp; e) if (r) is below apredefined value for each radio sferic, identifying a location of thelightning activity based upon the determined locations for the radiosferics; and f) if (r) is not below a predefined value for at least oneradio sferic, removing radio sferics from the collection of radio sfericdata that have a residual value (r) above the predefined value andreturning to step c).

Other aspects and advantages of the invention will become apparent fromthe following detailed description, taken in conjunction with theaccompanying drawings, illustrating the principles of the invention byway of example only.

BRIEF DESCRIPTION OF THE DRAWINGS

The advantages of the invention described above, together with furtheradvantages, may be better understood by referring to the followingdescription taken in conjunction with the accompanying drawings. Thedrawings are not necessarily to scale, emphasis instead generally beingplaced upon illustrating the principles of the invention.

FIG. 1 is a block diagram of a hybrid satellite and ground-based systemfor lightning location.

FIG. 2 is a Venn diagram showing overlap in detection between thesatellite and the ground-based sensors

FIG. 3 is a flow diagram of a first exemplary method of locatinglightning activity using the hybrid satellite and ground-based system.

FIG. 4 is a flow diagram of a method for determining if of radio sfericsconverges on a location using ground sensor-based location as an initialguess.

FIG. 5 is a diagram showing a comparison of a location of radio sfericsto a centroid location of a satellite group.

FIG. 6 is a flow diagram of a first exemplary method of locatinglightning activity using the hybrid satellite and ground-based system

FIGS. 7A and 7B are diagrams relating to identifying radio sferics fromground-based sensors that correspond to lightning

FIG. 8 is a flow diagram of a method for determining if of radio sfericsconverges on a location using satellite-based location as an initialguess.

FIG. 9 is a diagram that depicts optical energy of lightning pulses asdetected by the satellite and the electrical signals recorded by theground-based sensors.

FIG. 10 is a map showing the location of the lightning pulses asdetermined by the server computing device.

FIG. 11 is a screenshot of an exemplary user interface of anoperational, real-time map containing the satellite-ground hybridlightning location data as determined by the server computing device.

DETAILED DESCRIPTION

FIG. 1 is a block diagram of a hybrid satellite and ground-based system100 for lightning location. The system 100 comprises a satellite 102that captures a first set of data associated with a lightning flash 103,a plurality of ground-based sensors 104 a-104 e (collectively, 104) thatcapture a second set of data associated with a lightning flash, and aserver computing device 106 that is coupled to the satellite 102 and theground-based sensors 104 in order to receive data from the satellite 102and the ground-based sensors 104. The server computing device 106includes a database 108 for, e.g., storing and retrieving dataassociated with the techniques described herein. The satellite 102, theground-based sensors 104 and the server computing device 106 can bearranged to communicate via a communications network, e.g., in order toexchange data as described herein.

Exemplary ground-based sensors 104 include, but are not limited to,lightning detection sensors available from Earth Networks, Inc. ofGermantown, Md. In some embodiments, the sensors 104 are configured toconnect to the server computing device 106 via TCP/IP and transmitlightning data back to the server computing device at periodic intervals(e.g., every second).

Generally, the satellite 102 is used as the initial lightning locator,although both the satellite 102 and the ground-based sensors 104 seeslightly different signals at slightly different times. Both thesatellite 102 and the ground-based sensors 104 locate approximately thesame amount of lightning pulses over the U.S., but only about 60% ofthese located pulses match in time and space. FIG. 2 is a Venn diagramshowing the overlap in detection between the satellite 102 and theground-based sensors 104; the present system 100 provides locations,peak currents, and classifications for the lightning pulses in theoverlap region 202.

The system 100 of FIG. 1 can perform the above-referenced lightninglocation determination in two different ways:

1) Locate, Then Merge

In this embodiment, the satellite 102 and the ground-based sensors 104detect and locate lightning flashes independently, and transmit thelocation data to the server computing device 106. The server computingdevice 106 then compares the respective locations received from each ofthe satellite 102 and the ground-based sensors 104 to determine whichsignals are due to lightning, and which signals are due to noise. Forexample, the satellite data can be used to determine which of theground-based sensor locations are due to noise—which allows relaxationof normal noise reduction routines in the ground-based sensors 104 andthereby increase the number of matches.

FIG. 3 is a flow diagram of a first exemplary method 300 of locatinglightning activity, using the hybrid satellite and ground-based system100 of FIG. 1. The server computing device 106 receives (302) locationcoordinates and time data associated with detected lightning activityfrom satellite 102. The satellite detects lightning process (e.g.,groups of lightning flashes) in a geographic region on the ground usingone or more optical sensors. For example, the satellite 102 detectsoptical energy associated with the lightning process in a geographicregion (e.g., 10-20 km across) within a defined time window (e.g., 4ms). The satellite 102 records the approximate position (e.g., latitudeand longitude ±10 km) and time (e.g., timestamp ±4 ms) of the lightningprocess. The satellite 102 transmits the optical energy data, theapproximate position, and the time to the server computing device 106.

In the United States, for example, an exemplary satellite is operated bythe National Aeronautics and Space Administration (NASA), and includesan optical sensor that detects the light produced by lightning using alens and CCD sensor. In the case of the NASA satellite, five hundredlightning images of the planet are taken every second, with a ‘fulldisk’ field of view. Specifics of implementation vary for differentsatellites, but the algorithm described here works in all cases. Thesatellite data is quality checked and then is made available to theserver computing device 106 via standard internet connection (i.e.,TCP/IP). The satellite data typically arrives at the server computingdevice 106 approximately twenty to forty seconds after the lightningoccurs, in netCDF format. Generally, the satellite data arrives asevents (pixels from the camera sensors), groups (groups of spatiallycontiguous pixels in the same frame, 2 ms), and flashes (clusters ofgroups nearby in space and time). Each event is coded with its locationon the surface of the planet, and the time it occurred, along with otherinformation. Because certain quality controls are already applied, allsolutions coming from the satellite can be assumed to have been producedby lightning.

At approximately the same time, the server computing device 106 captures(304) lightning feature data (e.g., RF electromagnetic signal from thelightning) for lightning activity from at least one of the one or moreground-based lightning sensors 104 (e.g., ground radio sferic sensors).It should be appreciated that there are typically numerous ground-basedsensors (at least five, in practice hundreds) distributed over theregion of interest (in this case, the continental United States, butother regions exist, for example, Brazil, Europe, etc.) in knownlocations. These ground-based sensors detect the radio signal producedby lightning (radio sferic) and transmit the signal in digital form tothe server computing device 106 via standard internet protocol (i.e.,TCP/IP). In some embodiments, the server computing device 106 receivesdata from each sensor every second and the data can be transmitted in aproprietary digital format.

The server computing device 106 combines the radio sferic data receivedfrom the various ground-based sensors and processes the combined radiosferic data using a time of arrival triangulation algorithm to generate(306) a plurality of ground network point locations from the radiosferics. Each ground point location includes a location (latitude,longitude), classification (IC, CG), an estimated peak current(kiloamps), and an estimated location accuracy (kilometers). In someembodiments, the ground point location data is generated in JSON format.Ground-based sensor data arrives as pulses (location of a singleelectric field sferic), and flashes (clusters of pulses nearby in spaceand time).

FIG. 4 is a flow diagram of a method 400 for determining if the radiosferics converge on a location.

At step 402, the server computing device 106 finds peak times (tp) andsensor locations (ps) for each radio sferic;

At step 404, the server computing device 106 uses location (lat, lon)(p0) and time (t0) of the ground network point location as the initialguess location;

At step 406, the server computing device 106 uses a Levenberg-Marquardtalgorithm to find location (p) and time (t) which minimizes |t−D (p,ps)/c−tp| for all radio sferics—where D(p, ps) is the distance betweenlocations p and ps;

At step 408, the server computing device 106 calculates the residual (r)for all radio sferics: r=t−D(p, ps)/c−tp;

If r is small enough for all radio sferics, the server computing device106 has determined that the radio sferics have converged on a location.Otherwise, the server computing device 106 removes the radio sfericassociated with the largest residual r and goes back to step 406.

An exemplary time of arrival triangulation algorithm is described inU.S. Pat. No. 8,275,548, titled “Method and apparatus for detectinglightning activity,” which is incorporated herein by reference. In someembodiments, the time of arrival triangulation algorithm is modified toremove certain quality checking that is normally done, which producesmany more lightning location solutions but of course with far more falselocations. The false locations are removed during the matching phase asdescribed below.

The server computing device 106 waits for both the satellite 102 and theground-based sensors 104 to deliver locations for lightning, and thencompares (308) the determined location from the ground-based sensorradio sferic data and the location coordinates received from satellite102 to identify one or more sets of matched data. There are a number ofdifferent possibilities that can happen, as shown in FIG. 5, which is adiagram showing a comparison of a location of radio sferics to acentroid location of a satellite group.

Case 1: If the satellite 102 detects an event, and the ground-basedsensors 104 detect the same event within the defined time window (e.g.,+/−4 ms), and inside the event footprint defined by the satellite 102,the server computing device 106 considers this event a match (see 502 ofFIG. 5). In this case, the server computing device 106 augments (310)the satellite data (e.g., GLM group data) is using the location (lat,lon), peak current, and classification information from the ground-basedsensors 104.

Case 2: If the satellite 102 detects an event, and the ground-basedsensors 104 detect the same event within the defined time window (e.g.,+/−4 ms), and outside the event footprint defined by the satellite butwithin a defined threshold (e.g., 75 km), the server computing device106 considers these events to be related (see 504 of FIG. 5). Both thesatellite 102 and the ground-based sensors 104 are likely seeing thesame physical lightning process, but for some reason the solution to thelocation is not converging. In this case, the server computing device106 augments (310) the satellite data (e.g., GLM group data) with thepeak current and classification information from the ground-basedsensors 104.

Case 3: If the satellite 102 detects an event, but the ground-basedsensors 104 do not (or the ground-based location does not meet therequirements as set forth in Cases 1 and 2 above) (see 506 of FIG. 5),the server computing device 106 does not determine a match and theserver computing device 106 does not augment the satellite data (e.g.,GLM group data).

Generally, the output data generated by the server computing device 106is in netCDF format—similar to the format of the satellite 102 data, butwith some additional fields for the additional information. In someembodiments, the server computing device 106 makes the output dataavailable to further services, products, alerts, visualizations, andremote client computing devices (e.g., smartphones, tablets, smartwatches, IoT devices, and the like).

In some embodiments, matching is only done in one direction, i.e.,satellite data is used to determine which of the ground-based sensorlocations are due to noise, or ground data is used to determine which ofthe satellite-based sensor locations are due to noise.

In some embodiments, matching is done in both directions, i.e. grounddata is used to determine which satellite data is due to noise, andsatellite data is used to determine which ground data is based on noise.When matching is done in both directions, the number of ground-basedpoint locations which are matched to satellite-based area locations ismaximized.

2) Locate While Merging

In this embodiment, the satellite optical location is used as a priorguess for the ground-based sensor network solution. This greatlysimplifies the ground-based network solution, and maximizes theprobability of locating the lightning event while minimizing thecomputation time required.

FIG. 6 is a flow diagram of a second exemplary method 600 of locatinglightning activity, using the hybrid satellite and ground-based system100 of FIG. 1. The server computing device 106 captures (602) data(e.g., location coordinates and time data) from the optical sensor ofsatellite 102. As noted above, the satellite data is quality checked andthen is made available to the server computing device 106 via standardinternet connection (i.e., TCP/IP). The satellite data typically arrivesat the server computing device 106 approximately twenty to forty secondsafter the lightning occurs, in netCDF format. Generally, the satellitedata arrives as events (pixels from the camera sensors), groups (groupsof spatially contiguous pixels in the same frame, 2 ms), and flashes(clusters of groups nearby in space and time). Each event is coded withits location on the surface of the planet, and the time it occurred.Because certain quality controls are already applied, all solutionscoming from the satellite should be produced by lightning.

At approximately the same time, the server computing device 106 captures(604) lightning feature data (e.g., raw radio sferic data) from aplurality of sensors in the network of ground-based sensors 104 (e.g.,ground radio sferic sensors). As noted above, there are typicallynumerous ground-based sensors (at least five, in practice hundreds)distributed over the region of interest (in this case, the continentalUnited States, but other regions exist, for example, Brazil, Europe,etc.) in known locations. These ground-based sensors detect the radiosignal produced by lightning (radio sferic) and transmit the signal indigital form to the server computing device 106 via standard internetprotocol (i.e., TCP/IP). In some embodiments, the server computingdevice 106 receives data from each sensor every second and the data canbe transmitted in a proprietary digital format.

The server computing device 106 uses the satellite data to identify(606) one or more of the plurality of ground-based sensors 104 for whichportions of the radio sferics should have signals produced by lightning.In a preferred embodiment, the server computing device 106 identifies atleast four ground-based sensors 104 that observed the lightning processdetected by the satellite 102. The sensors can be identified based upon,e.g., distance from the approximate position of the lightning pulse asreceived from the satellite 102, and background noise level. In someembodiments, the system 100 can detect the radio signature of lightningabout 1,000 km out for most sensor sites, but this distance can beincreased if the noise level at the site is low (at best, around 2,000km). Also, the system can implement ionospheric bounces, which enablesthe detection of the signature of large events that are even furtheraway. In one example, the server computing device 106 uses a signalquality metric to evaluate the signal(s) detected by the sensors andcombines that with, e.g., range of the sensor to determine which sensorsites to pull lightning data from.

FIGS. 7A and 7B are diagrams relating to identifying radio sferics fromground-based sensors that correspond to lightning. The server computingdevice 106 obtains a satellite group (e.g., 402 in FIG. 7A) from, e.g.,a satellite data feed—the satellite group has a time (t0) and a locationlat, lon (p0). The server computing device 106 determines a distance (D)from the centroid of the satellite group 402 to all ground-based sensors(e.g., sensors 704 a-704 d in FIG. 7A). The server computing device 106then reads sferic data for all ground-based sensors that are closer thana certain distance (e.g., 1,000 km) from the centroid of the group(e.g., sensors 704 a-704 c in FIG. 7A).

The server computing device 106 determines the expected arrival time ofeach radio sferic as t0+D/c.

If a sensor detects a radio sferic within the window t0+D/c+/− apredetermined time window (e.g., 4 ms), this sensor is said to detectthe group.

If a sensor does not detect a radio sferic within the window t0+D/c+/−the predetermined time window (e.g., 4 ms), this sensor is said to notdetect the group.

If a sensor is too far away, the sferic data is not considered.

Exemplary radio sferic detection data for the sensors in FIG. 7A isshown in FIG. 7B. For example, the radio sferics for Sensor 1 704 a andSensor 2 704 b are within the time window, so the server computingdevice 106 classifies the sferic data for theses sensors 704 a-704 b asa detection. The radio sferic for Sensor 3 704 c is not within the timewindow, so the server computing device 106 classifies the sferic datafor Sensor 3 as a non-detection. And, Sensor 4 704 d is further than thedefined distance (e.g., 1,000 km) away from the satellite group, so theserver computing device 106 does not consider the sferic data for Sensor4.

The server computing device 106 generates as output a collection ofradio sferics associated with a satellite group. If the collectionincludes more than a certain number of radio sferics (e.g., four), thecollection is used by the server computing device 106 to determine (608)location of the lightning. It should be appreciated that the arrivaltime of the radio sferic in the window can vary slightly from sensor tosensor. This is expected, because the satellite group location has someerror in it. It is for this reason that the radio sferics can produce amore accurate location of the lightning process than the satellite.

The server computing device 106 determines if the collection of radiosferics converges on a location. FIG. 8 is a flow diagram of a methodfor determining if the collection of radio sferics converges on alocation.

At step 802, the server computing device 106 finds peak times (tp) andsensor locations (ps) for each radio sferic in the collection;

At step 804, the server computing device 106 uses group location (lat,lon) (p0) and time (t0) of the satellite group as the initial guesslocation. It should be appreciated that the initial guess t0, p0 in 804is much more accurate than the initial guess t0, p0 used in step 404 ofFIG. 4, causing the algorithm to converge faster.

At step 806, the server computing device 106 uses a Levenberg-Marquardtalgorithm to find location (p) and time (t) which minimizes |t−D(p,ps)/c−tp| for all radio sferics in the collection—where D(p, ps) is thedistance between locations p and ps;

At step 808, the server computing device 106 calculates the residual (r)for all radio sferics in the collection: r=t−D(p, ps)/c−tp;

If r is small enough for all radio sferics in the collection, the servercomputing device 106 has determined that the collection has converged ona location. Otherwise, the server computing device 106 removes the radiosferic associated with the largest residual r and goes back to step 806.

If the server computing device 106 determines that the collection hasconverged on a location, the location is compared to the centroidlocation of the satellite group—as shown in, and described above withrespect to, FIG. 5. If the collection location (black dot) is within adefined distance (e.g., 75 km) of the centroid location satellite group(grayscale squares) (502), the electric field sferic is deemed to havebeen produced by the same physical lightning process. The servercomputing device 106 uses the raw sferic data for the pulse to determinethe peak current and the classification (IC/CG) for this pulse, and theserver computing device 106 appends this information to the satellitegroup information.

If the collection location is within the bounds of the satellite group(504), in addition to the classification and peak current, the servercomputing device 106 also appends the location (lat, lon) determined bythe ground-based sensors 104 to the satellite group information.

If the collection does not converge on a location, or the location istoo far from the satellite group (506), or fewer than a certain numberof sensors detect the pulse (e.g., four), no information is appended tothe satellite group information.

Generally, the output data generated by the server computing device 106is in netCDF format—similar to the format of the satellite 102 data, butwith some additional fields for the additional information. In someembodiments, the server computing device 106 makes the output dataavailable to further services, products, alerts, visualizations, andremote client computing devices (e.g., smartphones, tablets, smartwatches, IoT devices, and the like).

Under either of the above embodiments, the server computing device 106can perform matching of the optical energy of the lightning pulses asdetected by the satellite and the electrical signals recorded by theground-based sensors.

FIG. 9 is a diagram that depicts optical energy of lightning pulses 902as detected by the satellite 102 and the electrical signals 904 recordedby the ground-based sensors 104. As shown in FIG. 9, the optical energyand the electrical signals do not match one-to-one. If the satellite 102and the ground-based sensors 104 detect a signal, and the ground-basedsensors 104 can locate the signal, the data are colored light gray(e.g., 906). If the ground-based sensors 104 cannot locate the signal,the data are colored dark gray (e.g., 908).

FIG. 10 is a map showing the location of the lightning pulses asdetermined by the server computing device 106. As shown in FIG. 10, theblack squares (e.g., 1002) show the locations of the optical pixels asseen by the satellite 102, and the light gray dots (e.g., 1004) are thelocations as determined by the ground-based sensors 104 using the hybridlocation technique described herein. Note that the clustering of thelight gray dots for the ground-based sensor locations is tighter thanthat of the black squares for the satellite pixels, so the locationaccuracy of the satellite data has been improved.

FIG. 11 is a screenshot of an exemplary user interface of anoperational, real-time map containing the satellite-ground hybridlightning location data as determined by the server computing device106. The server computing device 106 can generate the map (andassociated user interface) and transmit the map/UI to a remote computingdevice—such as client computing devices 102 a-102 n. In someembodiments, the map data is automatically updated at periodic intervals(e.g., every minute) by the server computing device 106. As shown inFIG. 11, the gray squares (e.g., 1102) show the locations of the opticalpixels as seen by the satellite 102, and the bowties (e.g., 1104) arethe locations as determined by the ground-based sensors 104 using thehybrid location technique described herein. Each bowtie also includesmetadata such as lightning flash type and amplitude. For example, a usercan view the metadata by interacting with the corresponding bowtie(e.g., by hovering over it or clicking it, which displays the metadatain a corner of the screen). It should be appreciated that otherconfigurations of the map/UI can be contemplated within the scope of thetechnology described herein. Again, note the tight clustering of theground-based sensor locations versus the gray squares of the satellitelocations.

Occasionally, the signals are detected by both the satellite andground-based sensors, but not well enough to get a location. In thiscase, the server computing device 106 can still provide classificationand amplitude of the pulse.

In one embodiment, as mentioned above, the server computing device 106can calculate the location using a ‘time difference of arrival’algorithm. In some embodiments, the server computing device 106 canimplement a more accurate (but, in some cases, computationally moreexpensive) Bayesian location technique. In one example, in regions thathave many ground-based sensors, the system can achieve a locationaccuracy of ˜100 m, while in regions with fewer ground-based sensors,the system can achieve a location accuracy of ˜2 km. In one example, theserver computing device 106 determines geographic coordinates (latitude,longitude) and time of the lightning process. The server computingdevice 106 also calculates other information about the lightningprocess, including peak current, type (e.g., intra-cloud,cloud-to-ground), and other metadata. In the event that fewer than fourground-based sensors 104 observe the lightning process (e.g., thelightning process occurred over the ocean), the server computing device106 can still calculate certain information about the lightning process,such as peak current and type.

As can be appreciated, the techniques described herein of usinglightning location data as detected by a satellite (also calledsatellite preconditioning) reduces the amount of computation needed tolocate the lightning process using only data from the ground-basedsensors 104 (for the ‘Locate While Merging’ implementation describedabove)—making the entire process more efficient, in some cases, by atleast a factor of ten. In the case of using a traditionaltime-of-arrival location algorithm, the initial guess of location asprovided by the satellite identifies which radio features are producedby a particular lightning process. This identification step is normallythe most computationally expensive portion of lightning location.Further, the satellite preconditioning described herein also limits thegeographic region in which the lightning process might be located. Thisallows other location techniques previously deemed computationallyimpractical, such as Bayesian location, to be employed, enablingincreased LA and accurate calculations of the lightning processaltitude—whereas previously, a Bayesian locator required computations tobe made in a volume around the expected source location. The larger thevolume is, the more calculations are required. By having an accurateinitial guess as provided by the hybrid system 100, these calculationscan be minimized. It is important to note that the combination ofsatellite lightning data and ground-based lightning data should be doneduring lightning location to realize all the benefits.

In some embodiments, the server computing device 106 includes an alertgeneration module (not shown). The alert generation module uses theanalyzed characteristics of the lightning data, including the locationinformation determined as described above, to automatically identifygeographical areas that may be impacted by severe weather associatedwith the lightning data.

To issue an alert that reaches persons and/or entities that may bedirectly affected by the severe weather or that may have an interest inthe affected area, the alert generation module determines one or moregeographical areas at risk based on the location information determinedfrom the satellite and ground-based sensor systems. In some embodiments,the alert generation module determines a warning area that correspondsto the current location of the lightning activity.

After determining one or more areas at risk, the alert generation moduleautomatically identifies a set of one or more remote devices that aremonitoring the at-risk areas and automatically transmits an alert to theremote devices. The remote devices can include computer-based devices,such as mobile phones and global positioning system (GPS) hardware. Theremote devices can also include other types of warning systems, such aslights, sirens and horns that are configured to connect to acommunications network. In some embodiments, the database 108 includesinformation related to identification of the remote devices (e.g., IPaddress, phone number, email address), and the alert generation moduleuses the identification information to prepare an alert for each remotedevice. The database 108 also includes information mapping theidentification of a remote device to a particular geographic area orareas that the remote device is monitoring (e.g., zip code, county name,street address). The alert generation module uses any standardcommunication protocol or technique, such as packet-based delivery(e.g., text messaging, XML, email), circuit-based delivery (e.g.,paging, voice messaging), and the like. For example, a user cansubscribe to receive alerts for a particular zip code on his mobilephone. The system 100 stores the user's telephone number in the database108. When the alert generation module identifies a geographic locationthat is at risk for severe weather and all or part of the identifiedlocation falls within the zip code submitted by the user, the alertgeneration module issues an alert (e.g., a text message, a voicemessage) addressed to the telephone number of the user's mobile phone.In this embodiment, the user's mobile phone need not be located in thesame geographic area as identified by the alert generation module as “atrisk.”

The server computing device 106 can transmit lightning-relatedinformation to any number of remote devices equipped or capable ofreceiving them. For example, the server computing device 106 cantransmit the information to a mobile device using standard communicationtechniques (e.g., cellular, wireless). As described above, the servercomputing device 106 can generate and issue severe weather alerts toremote devices—which allows for increased awareness of incoming severeweather. In some embodiments, the lightning data captured by the hybridtechnique described herein can be merged or combined with the proxylightning radar map visuals and data as described in U.S. Pat. No.9,891,345, titled “Using lightning data to generate proxy reflectivitydata,” which is incorporated herein by reference.

The above-described techniques can be implemented in digital and/oranalog electronic circuitry, or in computer hardware, firmware,software, or in combinations of them. The implementation can be as acomputer program product, i.e., a computer program tangibly embodied ina machine-readable storage device, for execution by, or to control theoperation of, a data processing apparatus, e.g., a programmableprocessor, a computer, and/or multiple computers. A computer program canbe written in any form of computer or programming language, includingsource code, compiled code, interpreted code and/or machine code, andthe computer program can be deployed in any form, including as astand-alone program or as a subroutine, element, or other unit suitablefor use in a computing environment. A computer program can be deployedto be executed on one computer or on multiple computers at one or moresites.

Method steps can be performed by one or more processors executing acomputer program to perform functions of the technology by operating oninput data and/or generating output data. Method steps can also beperformed by, and an apparatus can be implemented as, special purposelogic circuitry, e.g., a FPGA (field programmable gate array), a FPAA(field-programmable analog array), a CPLD (complex programmable logicdevice), a PSoC (Programmable System-on-Chip), ASIP(application-specific instruction-set processor), or an ASIC(application-specific integrated circuit), or the like. Subroutines canrefer to portions of the stored computer program and/or the processor,and/or the special circuitry that implement one or more functions.

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessors, andany one or more processors of any kind of digital or analog computer.Generally, a processor receives instructions and data from a read-onlymemory or a random access memory or both. The essential elements of acomputer are a processor for executing instructions and one or morememory devices for storing instructions and/or data. Memory devices,such as a cache, can be used to temporarily store data. Memory devicescan also be used for long-term data storage. Generally, a computer alsoincludes, or is operatively coupled to receive data from or transferdata to, or both, one or more mass storage devices for storing data,e.g., magnetic, magneto-optical disks, or optical disks. A computer canalso be operatively coupled to a communications network in order toreceive instructions and/or data from the network and/or to transferinstructions and/or data to the network. Computer-readable storagemediums suitable for embodying computer program instructions and datainclude all forms of volatile and non-volatile memory, including by wayof example semiconductor memory devices, e.g., DRAM, SRAM, EPROM,EEPROM, and flash memory devices; magnetic disks, e.g., internal harddisks or removable disks; magneto-optical disks; and optical disks,e.g., CD, DVD, HD-DVD, and Blu-ray disks. The processor and the memorycan be supplemented by and/or incorporated in special purpose logiccircuitry.

To provide for interaction with a user, the above described techniquescan be implemented on a computer in communication with a display device,e.g., a CRT (cathode ray tube), plasma, or LCD (liquid crystal display)monitor, for displaying information to the user and a keyboard and apointing device, e.g., a mouse, a trackball, a touchpad, or a motionsensor, by which the user can provide input to the computer (e.g.,interact with a user interface element). Other kinds of devices can beused to provide for interaction with a user as well; for example,feedback provided to the user can be any form of sensory feedback, e.g.,visual feedback, auditory feedback, or tactile feedback; and input fromthe user can be received in any form, including acoustic, speech, and/ortactile input.

The above described techniques can be implemented in a distributedcomputing system that includes a back-end component. The back-endcomponent can, for example, be a data server, a middleware component,and/or an application server. The above described techniques can beimplemented in a distributed computing system that includes a front-endcomponent. The front-end component can, for example, be a clientcomputer having a graphical user interface, a Web browser through whicha user can interact with an example implementation, and/or othergraphical user interfaces for a transmitting device. The above describedtechniques can be implemented in a distributed computing system thatincludes any combination of such back-end, middleware, or front-endcomponents.

The components of the computing system can be interconnected bytransmission medium, which can include any form or medium of digital oranalog data communication (e.g., a communication network). Transmissionmedium can include one or more packet-based networks and/or one or morecircuit-based networks in any configuration. Packet-based networks caninclude, for example, the Internet, a carrier internet protocol (IP)network (e.g., local area network (LAN), wide area network (WAN), campusarea network (CAN), metropolitan area network (MAN), home area network(HAN)), a private IP network, an IP private branch exchange (IPBX), awireless network (e.g., radio access network (RAN), Bluetooth, Wi-Fi,WiMAX, general packet radio service (GPRS) network, HiperLAN), and/orother packet-based networks. Circuit-based networks can include, forexample, the public switched telephone network (PSTN), a legacy privatebranch exchange (PBX), a wireless network (e.g., RAN, code-divisionmultiple access (CDMA) network, time division multiple access (TDMA)network, global system for mobile communications (GSM) network), and/orother circuit-based networks.

Information transfer over transmission medium can be based on one ormore communication protocols. Communication protocols can include, forexample, Ethernet protocol, Internet Protocol (IP), Voice over IP(VOIP), a Peer-to-Peer (P2P) protocol, Hypertext Transfer Protocol(HTTP), Session Initiation Protocol (SIP), H.323, Media Gateway ControlProtocol (MGCP), Signaling System #7 (SS7), a Global System for MobileCommunications (GSM) protocol, a Push-to-Talk (PTT) protocol, a PTT overCellular (POC) protocol, and/or other communication protocols.

Devices of the computing system can include, for example, a computer, acomputer with a browser device, a telephone, an IP phone, a mobiledevice (e.g., cellular phone, personal digital assistant (PDA) device,laptop computer, electronic mail device), and/or other communicationdevices. The browser device includes, for example, a computer (e.g.,desktop computer, laptop computer) with a World Wide Web browser (e.g.,Microsoft® Internet Explorer® available from Microsoft Corporation,Mozilla® Firefox available from Mozilla Corporation). Mobile computingdevice include, for example, a Blackberry®. IP phones include, forexample, a Cisco® Unified IP Phone 7985G available from Cisco Systems,Inc., and/or a Cisco® Unified Wireless Phone 7920 available from CiscoSystems, Inc.

Comprise, include, and/or plural forms of each are open ended andinclude the listed parts and can include additional parts that are notlisted. And/or is open ended and includes one or more of the listedparts and combinations of the listed parts.

One skilled in the art will realize the invention may be embodied inother specific forms without departing from the spirit or essentialcharacteristics thereof. The foregoing embodiments are therefore to beconsidered in all respects illustrative rather than limiting of theinvention described herein.

1. A computerized method of locating lightning activity, the methodcomprising: receiving, by a server computing device from a satellitethat detects lightning activity occurring in a geographic region,location coordinates and time data associated with lightning activitydetected by the satellite; capturing, by the server computing devicefrom at least one of one or more ground-based lightning sensors thatdetect lightning activity, lightning feature data for lightning activitydetected by the at least one of one or more ground-based lightningsensors; generating, by the server computing device, a plurality ofground point locations based upon the lightning feature data capturedfrom the ground-based lightning sensors; comparing, by the servercomputing device, the ground point locations and the locationcoordinates received from the satellite to identify one or more sets ofmatched data; augmenting, by the server computing device, for each setof matched data, the location coordinates for the lightning activityreceived from the satellite with the lightning feature data capturedfrom the ground-based sensors; and transmitting, by the server computingdevice, the augmented location coordinates for the lightning activity toone or more remote computing devices.
 2. The method of claim 1, whereinthe server computing device receives optical energy informationassociated with the detected lightning activity from the satellite. 3.The method of claim 1, wherein the lightning feature data captured fromthe ground-based lightning sensors comprises radio sferic data.
 4. Themethod of claim 3, wherein generating a plurality of ground pointlocations comprises combining the radio sferic data received from aplurality of the ground-based lightning sensors and processing thecombined data using a time of arrival triangulation algorithm togenerate the ground point locations.
 5. The method of claim 4, whereineach ground point location comprises a location, a classification, anestimated peak current, and an estimated location accuracy.
 6. Themethod of claim 4, wherein the comparing step comprises determining thata lightning event detected by one or more of the ground-based sensorsoccurred within a predetermined time of a lightning event detected bythe satellite and occurred within a predetermined distance from thelightning event detected by the satellite.
 7. The method of claim 6,wherein the augmenting step comprises appending geographic coordinates,peak current, and classification from the ground-based sensors to groupdata associated with the satellite.
 8. The method of claim 4, whereinthe comparing step comprises determining that a lightning event detectedby one or more of the ground-based sensors occurred within apredetermined time of a lightning event detected by the satellite,occurred outside a first predetermined distance from the lightning eventdetected by the satellite, and occurred inside a second predetermineddistance of the lightning event detected by the satellite.
 9. The methodof claim 8, wherein the augmenting step comprises appending peakcurrent, and classification from the ground-based sensors to group dataassociated with the satellite.
 10. The method of claim 4, wherein thecomparing step comprises determining that a lightning event detected byone or more of the ground-based sensors occurred outside of apredetermined time of a lightning event detected by the satellite oroccurred outside a predetermined distance from the lightning eventdetected by the satellite.
 11. The method of claim 10, wherein theaugmenting step comprises leaving group data associated with thesatellite unchanged.
 12. The method of claim 4, wherein generating aplurality of ground point locations further comprises: determining adistance from the location coordinates received from the satellite to alocation of each of the ground-based sensors; obtaining the radio sfericdata from each ground-based sensor that is located within apredetermined distance from the location coordinates received from thesatellite; determining an expected arrival time of the radio sferic dataobtained from the ground-based sensors; combining the radio sferic datathat has an expected arrival time within a predetermined threshold intoa collection of radio sferic data; and determining a location oflightning activity associated with the radio sferic data.
 13. The methodof claim 12, wherein determining a location of lightning activityassociated with the radio sferic data comprises: a) finding a peak time(tp) and a sensor location (ps) for each radio sferic in the collectionof radio sferic data; b) assigning the geographic coordinates (p0) andtime data (t0) received from the ground-based sensors as an initialguess location; c) determining location (p) and time (t) for each radiosferic in the collection of radio sferic data that minimizes |t−D(p,ps)/c−tp|; d) determining a residual value (r) for all radio sferics inthe collection of radio sferic data using the equation: r=t−D(p,ps)/c−tp; e) if (r) is below a predefined value for each radio sferic,identifying a location of the lightning activity based upon thedetermined locations for the radio sferics; and f) if (r) is not below apredefined value for at least one radio sferic, removing radio sfericsfrom the collection of radio sferic data that have a residual value (r)above the predefined value and returning to step c).
 14. A system forlocating lightning activity, the system comprising a server computingdevice including a memory for storing computer-executable instructionsand a processor for executing the computer-executable instructions, theprocessor executing the computer-executable instructions to: receive,from a satellite that detects lightning activity occurring in ageographic region, location coordinates and time data associated withlightning activity detected by the satellite; capture, from at least oneof one or more ground-based lightning sensors that detect lightningactivity, lightning feature data for lightning activity detected by theat least one of one or more ground-based lightning sensors; generate aplurality of ground point locations based upon the lightning featuredata captured from the ground-based lightning sensors; compare theground point locations and the location coordinates received from thesatellite to identify one or more sets of matched data; augment, foreach set of matched data, the location coordinates for the lightningactivity received from the satellite with the lightning feature datacaptured from the ground-based sensors; and transmit the augmentedlocation coordinates for the lightning activity to one or more remotecomputing devices.
 15. The system of claim 14, wherein the servercomputing device receives optical energy information associated with thedetected lightning activity from the satellite.
 16. The system of claim14, wherein the lightning feature data captured from the ground-basedlightning sensors comprises radio sferic data.
 17. The system of claim16, wherein generating a plurality of ground point locations comprisescombining the radio sferic data received from a plurality of theground-based lightning sensors and processing the combined data using atime of arrival triangulation algorithm to generate the ground pointlocations.
 18. The system of claim 17, wherein each ground pointlocation comprises a location, a classification, an estimated peakcurrent, and an estimated location accuracy.
 19. The system of claim 17,wherein the comparing step comprises determining that a lightning eventdetected by one or more of the ground-based sensors occurred within apredetermined time of a lightning event detected by the satellite andoccurred within a predetermined distance from the lightning eventdetected by the satellite.
 20. The system of claim 19, wherein theaugmenting step comprises appending geographic coordinates, peakcurrent, and classification from the ground-based sensors to group dataassociated with the satellite.
 21. The system of claim 17, wherein thecomparing step comprises determining that a lightning event detected byone or more of the ground-based sensors occurred within a predeterminedtime of a lightning event detected by the satellite, occurred outside afirst predetermined distance from the lightning event detected by thesatellite, and occurred inside a second predetermined distance of thelightning event detected by the satellite.
 22. The system of claim 21,wherein the augmenting step comprises appending peak current, andclassification from the ground-based sensors to group data associatedwith the satellite.
 23. The system of claim 17, wherein the comparingstep comprises determining that a lightning event detected by one ormore of the ground-based sensors occurred outside of a predeterminedtime of a lightning event detected by the satellite or occurred outsidea predetermined distance from the lightning event detected by thesatellite.
 24. The system of claim 23, wherein the augmenting stepcomprises leaving group data associated with the satellite unchanged.25. The system of claim 17, wherein generating a plurality of groundpoint locations further comprises: determining a distance from thelocation coordinates received from the satellite to a location of eachof the ground-based sensors; obtaining the radio sferic data from eachground-based sensor that is located within a predetermined distance fromthe location coordinates received from the satellite; determining anexpected arrival time of the radio sferic data obtained from theground-based sensors; combining the radio sferic data that has anexpected arrival time within a predetermined threshold into a collectionof radio sferic data; and determining a location of lightning activityassociated with the radio sferic data.
 26. The system of claim 25,wherein determining a location of lightning activity associated with theradio sferic data comprises: a) finding a peak time (tp) and a sensorlocation (ps) for each radio sferic in the collection of radio sfericdata; b) assigning the geographic coordinates (p0) and time data (t0)received from the ground-based sensors as an initial guess location; c)determining location (p) and time (t) for each radio sferic in thecollection of radio sferic data that minimizes |t−D(p, ps)/c−tp|; d)determining a residual value (r) for all radio sferics in the collectionof radio sferic data using the equation: r=t−D(p, ps)/c−tp; e) if (r) isbelow a predefined value for each radio sferic, identifying a locationof the lightning activity based upon the determined locations for theradio sferics; and f) if (r) is not below a predefined value for atleast one radio sferic, removing radio sferics from the collection ofradio sferic data that have a residual value (r) above the predefinedvalue and returning to step c).
 27. A computerized method of locatinglightning activity, the method comprising: receiving, by a servercomputing device from a satellite that detects lightning activityoccurring in a geographic region, location coordinates and time dataassociated with lightning activity detected by the satellite; capturing,by the server computing device from at least one of one or moreground-based lightning sensors that detect lightning activity, lightningfeature data for lightning activity detected by the at least one of oneor more ground-based lightning sensors; identifying, by the servercomputing device, at least one of the one or more ground-based lightningsensors in proximity to the geographic region based upon the locationcoordinates and time data received from the satellite; determining, bythe server computing device, a location of the lightning activity usingthe lightning feature data from the identified ground-based lightningsensors; and transmitting, by the server computing device, the locationof the lightning activity to one or more remote computing devices. 28.The method of claim 27, wherein the server computing device receivesoptical energy information associated with the detected lightningactivity from the satellite.
 29. The method of claim 27, wherein thelightning feature data captured from the ground-based lightning sensorscomprises radio sferic data.
 30. The method of claim 27, whereindetermining a location of the lightning activity comprises determiningthat a lightning event detected by one or more of the ground-basedsensors occurred within a predetermined time of a lightning eventdetected by the satellite and occurred within a predetermined distancefrom the lightning event detected by the satellite.
 31. The method ofclaim 30, further comprising appending geographic coordinates, peakcurrent, and classification from the identified ground-based sensors togroup data associated with the satellite.
 32. The method of claim 27,wherein the determining a location of the lightning activity comprisesdetermining that a lightning event detected by one or more of theground-based sensors occurred within a predetermined time of a lightningevent detected by the satellite, occurred outside a first predetermineddistance from the lightning event detected by the satellite, andoccurred inside a second predetermined distance of the lightning eventdetected by the satellite.
 33. The method of claim 32, furthercomprising appending peak current, and classification from theidentified ground-based sensors to group data associated with thesatellite.
 34. The method of claim 27, wherein determining a location ofthe lightning activity comprises determining that a lightning eventdetected by one or more of the ground-based sensors occurred outside ofa predetermined time of a lightning event detected by the satellite oroccurred outside a predetermined distance from the lightning eventdetected by the satellite.
 35. The method of claim 34, furthercomprising leaving group data associated with the satellite unchanged.36. The method of claim 27, wherein identifying at least one of the oneor more ground-based lightning sensors in proximity to the geographicregion comprises: determining a distance from the location coordinatesreceived from the satellite to a location of each of the ground-basedsensors; obtaining the radio sferic data from each ground-based sensorthat is located within a predetermined distance from the locationcoordinates received from the satellite; determining an expected arrivaltime of the radio sferic data obtained from the ground-based sensors;and combining the radio sferic data that has an expected arrival timewithin a predetermined threshold into a collection of radio sferic data.37. The method of claim 36, further comprising: a) finding a peak time(tp) and a sensor location (ps) for each radio sferic in the collectionof radio sferic data; b) assigning the geographic coordinates (p0) andtime data (t0) received from the ground-based sensors as an initialguess location; c) determining location (p) and time (t) for each radiosferic in the collection of radio sferic data that minimizes |t−D(p,ps)/c−tp|; d) determining a residual value (r) for all radio sferics inthe collection of radio sferic data using the equation: r=t−D(p, ps)/c−tp; e) if (r) is below a predefined value for each radio sferic,identifying a location of the lightning activity based upon thedetermined locations for the radio sferics; and f) if (r) is not below apredefined value for at least one radio sferic, removing radio sfericsfrom the collection of radio sferic data that have a residual value (r)above the predefined value and returning to step c).
 38. A system forlocating lightning activity, the system comprising a server computingdevice including a memory for storing computer-executable instructionsand a processor for executing the computer-executable instructions, theprocessor executing the computer-executable instructions to: receive,from a satellite that detects lightning activity occurring in ageographic region, location coordinates and time data associated withlightning activity detected by the satellite; capture, from at least oneof one or more ground-based lightning sensors that detect lightningactivity, lightning feature data for lightning activity detected by theat least one of one or more ground-based lightning sensors; identify atleast one of the one or more ground-based lightning sensors in proximityto the geographic region based upon the location coordinates and timedata received from the satellite; determine a location of the lightningactivity using the lightning feature data from the identifiedground-based lightning sensors; and transmit the location of thelightning activity to one or more remote computing devices.
 39. Thesystem of claim 38, wherein the server computing device receives opticalenergy information associated with the detected lightning activity fromthe satellite.
 40. The system of claim 38, wherein the lightning featuredata captured from the ground-based lightning sensors comprises radiosferic data.
 41. The system of claim 38, wherein determining a locationof the lightning activity comprises determining that a lightning eventdetected by one or more of the ground-based sensors occurred within apredetermined time of a lightning event detected by the satellite andoccurred within a predetermined distance from the lightning eventdetected by the satellite.
 42. The system of claim 41, furthercomprising appending geographic coordinates, peak current, andclassification from the identified ground-based sensors to group dataassociated with the satellite.
 43. The system of claim 38, whereindetermining a location of the lightning activity comprises determiningthat a lightning event detected by one or more of the ground-basedsensors occurred within a predetermined time of a lightning eventdetected by the satellite, occurred outside a first predetermineddistance from the lightning event detected by the satellite, andoccurred inside a second predetermined distance of the lightning eventdetected by the satellite.
 44. The system of claim 43, furthercomprising appending peak current, and classification from theidentified ground-based sensors to group data associated with thesatellite.
 45. The system of claim 38, wherein determining a location ofthe lightning activity comprises determining that a lightning eventdetected by one or more of the ground-based sensors occurred outside ofa predetermined time of a lightning event detected by the satellite oroccurred outside a predetermined distance from the lightning eventdetected by the satellite.
 46. The system of claim 45, furthercomprising leaving group data associated with the satellite unchanged.47. The system of claim 38, wherein identifying at least one of the oneor more ground-based lightning sensors in proximity to the geographicregion comprises: determining a distance from the location coordinatesreceived from the satellite to a location of each of the ground-basedsensors; obtaining the radio sferic data from each ground-based sensorthat is located within a predetermined distance from the locationcoordinates received from the satellite; determining an expected arrivaltime of the radio sferic data obtained from the ground-based sensors;and combining the radio sferic data that has an expected arrival timewithin a predetermined threshold into a collection of radio sferic data.48. The system of claim 47, further comprising: a) finding a peak time(tp) and a sensor location (ps) for each radio sferic in the collectionof radio sferic data; b) assigning the geographic coordinates (p0) andtime data (t0) received from the ground-based sensors as an initialguess location; c) determining location (p) and time (t) for each radiosferic in the collection of radio sferic data that minimizes |t−D(p,ps)/c−tp|; d) determining a residual value (r) for all radio sferics inthe collection of radio sferic data using the equation: r=t−D(p,ps)/c−tp; e) if (r) is below a predefined value for each radio sferic,identifying a location of the lightning activity based upon thedetermined locations for the radio sferics; and f) if (r) is not below apredefined value for at least one radio sferic, removing radio sfericsfrom the collection of radio sferic data that have a residual value (r)above the predefined value and returning to step c).